Personalização de programas de TV no contexto da TV digital portátil interativa

Abstract

Interactive Digital Television allows several services to be offered to users, in order to provide entertainment, e-learning and new mechanisms for social inclusion. Broadcasters and TV shoes may be created, which may gradually increase the amount of information to be displayed on the screen. As a result, users may experience discomfort and difficulties in finding information that really matters. In a portable environment, the user wants to make the most of his time when watching TV. Thus, investing too much time in searching for TV shows of interest is something undesirable. Recommender systems are used to minimize such shortcomings, help users with their searches for contents of interest and also to reduce the time spent on searches. This study focused on the development of a hybrid recommender system called BIPODiTVR, which is able to make recommendations from the observation of users behavior while watching television on the portable device. This system recommends TV shows through a collaborative and content-based filtering. The proposed system was evaluated by using metrics of acceptability of recommender systems applied to data provided by IBOPE, from six households for the period of fifteen days.